🚨 This article is a long-read, so get comfortable and feel free to use table of contents on the right to navigate the topics. Enjoy!
Key takeaways
- Data visualization in medical solutions can save time for both doctors and patients, detect patterns and errors, educate patients, and help make faster, more data-driven decisions.
- Key challenges in medical data visualization are data integration from multiple sources, security protocols, and interpretation technologies.
- Data visualization has transformed the healthcare industry by minimizing errors and bringing down operational costs.
What is data visualization
Data visualization is the art of organizing and presenting complex data in simple and easy-to-understand graphic elements. These practices help to illustrate relationships between various numerical indicators and help monitor information in real-time toor make data driven decisions.
Examples of data visualization tools include dashboards, graphs, maps, infographics, etc.
Data visualization is adopted across various industries. From the finances and healthcare sector to education and entertainment.
Salesforce, the biggest CRM platform, helps users organize financial and sales data
The medical sector especially benefits from data visualization, for example, enhancing overall healthcare provision, improving patient care, helping medical staff identify patterns and abnormalities, as well as adopting fraud detection in an organization.
How is data visualization used in healthcare: 3 examples
Imagine, you have 150 patients, who each took a blood panel test with 10 different indicators. All together it’s already 1500 different bits of data, not to mention other test results or cases with a bigger pool of patients. This amount of information needs to be organized, not only for a patient’s comfort but also for doctors, to be more efficient.
There are a number of ways you can present complex data in medical apps and web portals.
Interactive dashboards with patient info
A dashboard is a panel that presents data from various sources in one place. Let’s take a hospital portal as an example, there can be both: a patient-side panel and a doctor-side panel to track, for both sides to analyze and interpret the patient’s records.
Modern dashboards display real-time data and provide users with AI-assisted data integration, chart generation, and data analysis. Machine learning technologies help to recognize trends in data and generate actionable insights for users to improve their health and overall well-being.
For Biogeek, we developed an intuitive dashboard with the accent color highlighting all important elements
Interactive widgets
Widgets are graphic elements of the user interface that display information and provide a way for users to interact with them. All iPhone users are familiar with widgets, as Apple introduced them on the Lock Screen in iOS 14.
Most users are already familiar with widgets through Home Screens on their smartphones
In medical data visualization, widgets can be used as an alternative to traditional graphs and charts. Through interactive reports and widgets, a user can access data faster, refresh, and customize it for more actionable insights.
Custom filters
When dealing with large amounts of medical data, filters are essential to help users navigate through numbers and charts on dashboards. It seems obvious, but in our experience, this tool is often overlooked even in modern interactive apps.
Imagine a situation, where a physician needs to analyze treatment responses and retrieve patient data for a specific age group, medical condition, and treatment outcome. Custom filters allow them to effortlessly filter the data to a specific set, such as female patients, aged 40-60, with diabetes, who responded positively to a particular medication or treatment.
Utilizing filters helps users make decisions faster, while improving patient care by targeting specific subset of the data. Imagine the man hours saved, compared to a physician asking could have asked an administrator to go through EHRs manually select the patients that meet the criteria.
Custom filters in the medical software enable users to extract the exact information they need, based on their unique requirements. Ultimately, it leads to reduced operational costs, improved diagnostics, treatments, and overall healthcare outcomes.
On Apple Health, a user can customize the dashboard and filter data by various indicators
4 benefits of healthcare data visualization
Data visualization brings new ways to significantly enhance patient care and streamline medical processes for healthcare professionals. Let’s dive into 4 evident benefits of smart ways to use visual representation with medical information.
Saves time for patients and doctors
First of all, the most impactful advantage of health data visualization is the time-saving for both patients and healthcare professionals. When you present data in a clear and intuitive way, there is less need for long explanations and prescriptive analysis.
Patients can quickly find insights related to their medical conditions, test results, patient health status, and treatment plans. This enables them to be more engaged and informed in their health journeys. While at the same time, healthcare professionals can use visuals to explain diagnosis and treatment options, instead of time-consuming manual reporting and analysis.
Detects patterns and errors
Data visualization in healthcare provides doctors with an opportunity to identify patterns and immediately notice if anomalies or diseases occur. For example, if a patient experiences and starts logging symptoms, the doctor can compare it with illness patterns of other cases and deliver a diagnosis much faster.
By transforming big data into comprehensible graphs, charts, and maps, healthcare providers can observe trends and correlations that point to potential medical concerns.
These visual and intuitive data analytics not only help with early disease detection, but also with flagging incorrect test results, current patient health status, medication reactions, among other critical errors. This technology was widely used during the global pandemic to detect the rise of cases in particular cities and provide early warnings for officials and residents.
CDC still uses data visualization to report cases and predict trends
This kind of proactive approach to data visualization in healthcare can mean improved patient outcomes, reduced medical errors, and enhanced quality of care across healthcare organizations.
Educates patients
Medical providers can use health data visualization to increase patients’ awareness of everyday operations and diagnostic analysis processes. For example, Apple Health visualizes all its information to help users get more engaged and aware of their own well-being. It gathers data points from smart devices and a phone, presenting them in the form of charts and graphs with a short commentary.
Apple Health provides a commentary to data visualization to educate users about patterns and trends
Data visualization tools help foster a deeper understanding of medical information among patients. Complex medical concepts, treatment options, and procedural details can all be challenging for patients to grasp solely through a conversation with a doctor or text-heavy records.
Interactive diagrams, animated graphics, and personalized charts, helps patients understand their medical conditions.
This enhanced understanding leads to a stronger decision making process, helping patients comply with treatment plans, learn about prevention methods and actively participate in disease management.
Helps make decisions faster
In the fast-paced healthcare industry, timely decision-making is critical. Human life can literally depend on how fast healthcare organizations and specialists can detect and react to what’s going on. There are even cases, imagine during surgery or when patients are in critical condition, when every second counts.
Therefore, healthcare data needs to be presented in a clear and concise manner, so medical staff can swiftly assess test results, treatment responses, and historical data on intuitive dashboards. This enables them to make accurate diagnoses and recommend treatments.
Even non-urgent cases, healthcare data visualization can help with solving administrative tasks, allocating resources more efficiently, and planning operational expenses. For instance, when hospital management systems have information about regular check-ups, they can predict recurring appointments and adjust doctor’s schedules accordingly.
4 benefits memo
Below we summarized key benefits of data visualization in healthcare.
| Saves time for patients and doctors | When you present data in a clear and intuitive way, there is no need for long explanations and analysis. |
| Detects patterns and errors | By transforming data into comprehensible graphs, charts, and maps, doctors can observe trends and patterns that point to potential medical concerns. |
| Educates patients | Data visualization helps to increase patients’ awareness of everyday operations and diagnostic analysis processes |
| Helps make decisions faster | When healthcare data is presented in a clear and concise manner, medical staff can swiftly assess test results, and make accurate diagnoses. |
3 challenges healthcare organizations face when visualizing data
Healthcare sector is unforgiving to mistakes: just one case of negligence or human error can destroy a reputation of a hospital or a medical provider. Would you trust a clinic knowing that it had a data breach in the past? Less likely
To avoid any complications, it’s important to be aware of challenges you can face, and prepare in advance. Let’s discuss 3 points you need to be aware of when working on healthcare data visualization.
Complex data integration
One of the main challenges healthcare organizations face when visualizing data analytics is the diverse data sources. The healthcare sector generates vast amounts of medical data from electronic health records (EHRs), smart devices, smartphones phones, patient monitoring systems, and more. Often, this big data is stored in different formats, databases, and locations. This makes the process of aggregating and organizing it a complicated and prolonged task.
The challenge is to develop robust data integration pipelines that can handle data points from different sources, while ensuring accuracy, consistency, and real-time availability. Failure to overcome this challenge can result in compromising patient care, loyalty, and trust. Which is the main currency in the healthcare industry.
Data privacy and security
The security of medical data is paramount in the healthcare sector, considering the sensitive nature of personal information. Prescriptions, test results, and diagnoses should all be carefully protected information, meant for doctor and patient. When visualizing data, healthcare organizations must navigate regulatory compliance with laws such as HIPAA (also known as the Health Insurance Portability and Accountability Act) to safeguard patient privacy.
Some states, like California, have additional regulations for apps with healthcare data. For example, under California Consumer Privacy Act (CCPA), users have the right to know what information an app collects and to request information to be deleted.
Revolut, a global neo-bank, offers users to blur their balance when they are taking screenshots or showing an app to others. Why don’t medical apps adopt the same feature for sensitive data?
The main challenge is to find a balance between maintaining the anonymity of patients (for example, when lab technicians export the results), while marking sure you have enough information for visual display.
Finding a balance between providing insightful medical data and protecting patient confidentiality requires deep research, encryption, access controls, and frequent technical audits. As we noted earlier, breaches of data privacy can lead to serious legal and reputational consequences. So, make sure you talk it through with your custom software development team.
Users with different knowledge levels
While healthcare data visualization offers numerous benefits, it introduces the challenge of effectively communicating complex healthcare analytics to various stakeholders.
Doctors, hospital staff, administrators, and patients all have different levels of expertise and familiarity with data analysis and public health. For example, acute respiratory illness may sound extremely serious, but in common terms, it’s just the flu.
Designing data visualization tools that are both informative for doctors and easy to understand for patients can be a delicate task. Overly complicated terms and elements can lead to confusion and misinterpretation, while overly simplistic ones might fail to capture the nuances of the data.
As experienced developers in dealing with these matters, we recommend prioritizing clarity, relevance, and user-centered design with data analytics to ensure your solution truly empowers healthcare and informed decision-making.
How is data visualization transforming the healthcare industry
It’s fair to say that healthcare data visualization is revolutionizing the industry. Many market leaders have adopted interactive widgets, dashboards, charts, and other graphic elements in their interfaces. Your app should ride this wave with your customers.
Here are 2 key reasons why real time data visualization has emerged as a game-changer, offering benefits that redefine the way clinics and major hospitals operate.
It minimized human errors
Healthcare data visualization helps doctors to identify patterns, anomalies, and trends that might indicate potential issues. What’s important to know is that it reduces the number of mistakes public health professionals make.
According to research, the most common causes of medical errors are poor communication and inadequate information flow between medical practitioners. Whether verbal or written, between a physician, nurse, healthcare team member, or patient, it can have serious consequences.
Healthcare data visualization can automate some processes, and involve machine learning in establishing early detection and clear communication between wards.
On top of that, predictive medical visualization helps providers avoid repetitive tests and procedures, reducing the risk of duplication errors.
When doctors make precise decisions based on data, it cultivates a culture of data preparation, fostering accuracy and responsibility. This ultimately leads to improved patient care visualization.
It brought down the operational cost
Medical errors cost healthcare providers approximately $20 billion annually.
Traditional manual processes, repetitive tests and consultations, paper-based recordkeeping, and redundant administrative tasks are all notorious for their inefficiency and associated costs. All of it only leads to confusion with healthcare data, miscommunications, and, ultimately, medical errors.
Through data visualization, healthcare organizations can gain insights into resource allocation, patient flow, and operational bottlenecks. This enables smarter strategic planning that optimizes staffing, streamlines workflows, and minimizes waste.
Additionally, descriptive analytics powered by smart data visualization can predict patient demand and future diagnoses (like seasonal flu peaks). Knowing that, hospital managers can allocate resources more effectively, and enhance operational efficiency.
Overall, healthcare data visualization contributes to lower expenses, allowing organizations to redirect resources toward training programs for personnel, improved patient care, and innovation.
4 tools of data visualization in healthcare
To visualize data and create motion graphic infographics, you don’t need extensive coding experience. There are plenty of tools that will do it for you, here is a quick overview of the 4 most popular services for healthcare data visualization.
Tableau
Tableau is an American company named after its main product, a powerful data visualization tool. It was established in 2003 and bought by Salesforce in 2019.
Tableau allows users to create interactive and dynamic visualizations from various data sources through machine learning and personalized insights. Its user-friendly interface enables both beginners and experts to design insightful dashboards, charts, and graphs. What stands out about Tableau is its ability to handle large datasets and provide real-time insights, making it a go-to choice for data-driven decision-making across industries.
Tableau desktop interface
Infogram
Infogram, owned by Prezi Inc., is a creative alternative to Microsoft PowerPoint. Infogram is a versatile tool designed for creating visually appealing infographics and interactive charts. With a focus on simplicity, it offers a range of customizable templates and design options. Infogram suits content creators, marketers, and educators who want to convey complex information in a visually engaging manner, making data more accessible and comprehensible to a wider audience.
Infogram’s interface with a dashboard
ChartBlocks
ChartBlocks is an online platform dedicated to building charts and graphs with ease. If you have ever worked with Canva, you will intuitively know how to use the service.
ChartBlocks offers hundreds of designs and templates, as well as drag-and-drop functionality, so need for extensive technical skills. It’s an ideal choice for those seeking simple yet effective visual representations, suitable for individuals and small businesses, and it’s free!
Online chart builder in ChartBlocks
SAS Visual Analytics
SAS Visual Analytics is an enterprise-grade solution tailored for advanced data visualization and data analytics. It caters to organizations dealing with complex datasets, offering sophisticated interactive visualizations, predictive modeling, and data exploration capabilities. Though it’s not a perfect fit for smaller hospitals and clinics, the tool is important to know about. SAS as a company started in the 1960-70s, so Visual Analytics is a pioneer of the data visualization market.
SAS Visual Analytics empowers data professionals to uncover deep insights, patterns, and trends, aiding strategic decision-making and actionable insights across diverse sectors.
SAS Visual Analytics interface is quite simple, but it has proved itself over the years with big corporations and enterprises
How to implement data visualization in your healthcare software
Implementing data visualization in custom software development requires a strategic approach to ensure its effectiveness and usability.
Firstly, identify the key data points and metrics that are critical for medical professionals, administrators, and patients to visualize. Collaborate closely with medical experts to understand their needs and preferences in order to develop an interface that will assist with predictive analysis.
Choose appropriate visualization techniques such as graphs, charts, heatmaps, and interactive dashboards that best represent the healthcare data’s insights.
Ensure seamless integration with the existing medical technology, maintaining data security and privacy protocols. Prioritize user experience by designing intuitive interfaces and enabling customization options.
Regularly gather feedback from users to refine and enhance the visualizations, adapting healthcare data to evolving requirements.
When technical know-how is combined with a profound understanding of healthcare workflows, incorporating data visualization can make healthcare software more powerful. This helps make smarter decisions and improves patient care.
Wrapping up
Data visualization is an important step in building medical software. By offering a multitude of advantages, it revolutionized the medical industry. From saving time for both patients and doctors to uncovering hidden patterns, educating patients, and facilitating smooth decision-making.
But any healthcare solution which deals with sensitive information is unforgiving to mistakes. To avoid data breaches, potential complaints, and challenges, we recommend considering these 3 factors:
- Complex data integration, arranging information from multiple resources;
- Data security and privacy regulations (such as HIPAA);
- Users with different knowledge levels (from experienced doctors to administrators and patients).
As technology continues to evolve, data visualization will remain a cornerstone of modern healthcare, enhancing communication, driving efficiency, and ultimately, improving patient outcomes.
About us
Purrweb is a team of over 190 experts with diverse skill sets and knowledge in custom cross-platform software development, UI/UX design, and user mapping journey. We help startups and existing businesses build and test MVPs within 4 months.
Purrweb has deep domain expertise in healthcare app development and medical data visualization. We created Biogeek, a web app with a mobile adaptation that helps users keep all their laboratory tests in one place and access health monitoring insights in a couple of clicks.
On top of that, our team has extensive knowledge and experience with HIPAA and GDPR regulations for web and mobile apps.
